SOTAVerified

Time Series Analysis

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

Showing 11261150 of 6748 papers

TitleStatusHype
Predicting Temperature of Major Cities Using Machine Learning and Deep Learning0
From Text to Trends: A Unique Garden Analytics Perspective on the Future of Modern Agriculture0
ISLAND: Interpolating Land Surface Temperature using land coverCode0
A detection analysis for temporal memory patterns at different time-scales0
Learning Beyond Similarities: Incorporating Dissimilarities between Positive Pairs in Self-Supervised Time Series Learning0
Agriculture Credit and Economic Growth in Bangladesh: A Time Series Analysis0
PhysioZoo: The Open Digital Physiological Biomarkers Resource0
Time Series Analysis of Urban Liveability0
Predicting Financial Market Trends using Time Series Analysis and Natural Language Processing0
Evaluating Explanation Methods for Multivariate Time Series ClassificationCode0
Hierarchical Time Series Forecasting with Bayesian Modeling0
High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods0
Path Signatures for Seizure Forecasting0
Distinguishing Risk Preferences using Repeated Gambles0
The Bayesian Context Trees State Space Model for time series modelling and forecasting0
TimePool: Visually Answer "Which and When" Questions On Univariate Time Series0
Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis0
Forecasting, capturing and activation of carbon-dioxide (CO_2): Integration of Time Series Analysis, Machine Learning, and Material Design0
U-shaped Transformer: Retain High Frequency Context in Time Series Analysis0
Multivariate Time Series characterization and forecasting of VoIP traffic in real mobile networks0
A Deep Dive into Perturbations as Evaluation Technique for Time Series XAICode0
An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification0
A Novel Site-Agnostic Multimodal Deep Learning Model to Identify Pro-Eating Disorder Content on Social Media0
Exploring Spatial-Temporal Variations of Public Discourse on Social Media: A Case Study on the First Wave of the Coronavirus Pandemic in Italy0
Multivariate Time Series Early Classification Across Channel and Time DimensionsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47Unverified
2GRU-D - APC (n = 1)F127.3Unverified
3GRU-APC (n = 1)F125.7Unverified
4GRU-DF122.5Unverified
5GRUF122.3Unverified
6GRU-SimpleF122.2Unverified
7GRU-MeanF122.1Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51Unverified
2ViT% Test Accuracy98.11Unverified
3FlexTCN-4% Test Accuracy97.73Unverified
4MatchboxNet% Test Accuracy97.4Unverified
5CKCNN (100k)% Test Accuracy95.27Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13Unverified